#!/usr/bin/env python3 """Paired frozen-model Level-1/Level-2 ModeBench pass@8 evaluation.""" from __future__ import annotations import argparse,hashlib,itertools,json,os,re,sys,tempfile from datetime import datetime,timezone from pathlib import Path from typing import Any ROOT=Path(__file__).resolve().parents[1] sys.path.insert(0,str(ROOT/'src')) def sha(value:Any)->str: return hashlib.sha256(json.dumps(value,sort_keys=True,separators=(',',':')).encode()).hexdigest() def file_sha(path:Path)->str: h=hashlib.sha256() with path.open('rb') as f: for chunk in iter(lambda:f.read(1<<20),b''): h.update(chunk) return h.hexdigest() def atomic(path:Path,payload:Any)->None: path.parent.mkdir(parents=True,exist_ok=True) fd,tmp=tempfile.mkstemp(prefix='.'+path.name+'.',dir=path.parent) try: with os.fdopen(fd,'w') as f: json.dump(payload,f,indent=2,sort_keys=True); f.write('\n') os.replace(tmp,path) except BaseException: os.unlink(tmp); raise def args(): ap=argparse.ArgumentParser(description=__doc__) ap.add_argument('--domain',required=True) ap.add_argument('--model',type=Path,required=True) ap.add_argument('--model-label',required=True,choices=('qwen-0.5b','falcon-1b')) ap.add_argument('--level2-root',type=Path,default=ROOT/'var/data/modebench_harder_v2_matched') ap.add_argument('--output',type=Path,required=True) ap.add_argument('--seed',type=int,required=True) ap.add_argument('--temperature',type=float,default=1.0) ap.add_argument('--top-p',type=float,default=1.0) ap.add_argument('--max-tokens',type=int,default=192) ap.add_argument('--max-model-len',type=int,default=1024) ap.add_argument('--batch-size',type=int,default=8) ap.add_argument('--dtype',choices=('float16','bfloat16'),default='float16') ap.add_argument('--prompt-profile',choices=('boxed_direct_v1','deliberate_domain_v2','structured_solver_v3','hybrid_solver_v4','countdown_fewshot_v5','countdown_shallow_v6'),default='boxed_direct_v1') ap.add_argument('--row-limit',type=int,default=0,help='development-only calibration limit; zero means all 128 rows') ap.add_argument('--syntax-profile',choices=('none','pantry_legal_v1','domain_legal_v1','domain_legal_v2','countdown_legal_v3'),default='none') return ap.parse_args() def prompt_messages(domain:str,problem:str,profile:str)->list[dict[str,str]]: if profile=='countdown_shallow_v6': if domain!='countdown': raise ValueError('countdown_shallow_v6 is Countdown-only') system=('Use every supplied number exactly once and hit the target exactly. ' 'First test permutations of paired products a*b+c*d or a*b-c*d, ' 'paired sums (a+b)*(c+d) or (a+b)*(c-d), and one product ' 'a*b followed by adding or subtracting c and d. ' 'Return only one fully parenthesized expression inside \\boxed{}.') return [{'role':'system','content':system},{'role':'user','content':problem}] if profile=='countdown_fewshot_v5': if domain!='countdown': raise ValueError('countdown_fewshot_v5 is Countdown-only') system=('Solve the arithmetic target exactly. Use every supplied number exactly once. ' 'Return only one fully parenthesized expression inside \\boxed{}.') return [ {'role':'system','content':system}, {'role':'user','content':'Using the numbers [2, 3, 4], create an arithmetic expression that equals 14. Use each given number exactly once.'}, {'role':'assistant','content':'\\boxed{(2 + (3 * 4))}'}, {'role':'user','content':'Using the numbers [2, 3, 4, 5], create an arithmetic expression that equals 26. Use each given number exactly once.'}, {'role':'assistant','content':'\\boxed{((2 * 3) + (4 * 5))}'}, {'role':'user','content':problem}, ] if profile=='boxed_direct_v1': system='Return only the final answer inside \\boxed{}. Do not explain.' return [{'role':'system','content':system},{'role':'user','content':problem}] deliberate={ 'countdown':'Systematically combine every supplied number exactly once using +, -, *, /, and parentheses. Check the exact target before answering.', 'python_factors':'Construct one allowed lambda expression. Test small divisors with nested conditional expressions, for example 2 if n % 2 == 0 else 3 if n % 3 == 0 else 5, but adapt the tests to every listed case.', 'mathir':'Execute candidate menu actions exactly on both sides, simplify after each action, and check that the final state isolates x. Return action IDs, not x.', 'pantry':'Silently enumerate allowed stepped quantities for 2 to 4 non-forbidden ingredients, total every nutrient exactly, and check all bounds.', 'graph_coloring':'Check every edge after assigning the hidden vertices.', } structured={ 'countdown':'Search systematically over pairwise combinations until every number is used exactly once. Verify the arithmetic and output exactly the boxed expression.', 'python_factors':'Output exactly a boxed lambda. A reliable form is d1 if n == c1 else d2 if n == c2 else d3 if n == c3 else d4, choosing each di as a proper divisor of ci.', 'mathir':'Use algebraic isolation: move the right-side x term left, remove the left constant, then divide by the combined coefficient. Match those operations to the shuffled menu IDs.', 'pantry':'Prefer allowed high-energy/protein, very-low-sodium ingredients, especially seeds or oats. Choose stepped amounts, check every bound, and output 2 to 4 ingredient_id=grams pairs.', 'graph_coloring':'Check every edge after assigning the hidden vertices.', } if profile=='deliberate_domain_v2': guidance=deliberate[domain] elif profile=='structured_solver_v3': guidance=structured[domain] else: guidance={ 'countdown':deliberate['countdown']+' Output exactly the boxed expression.', 'python_factors':deliberate['python_factors']+' You may instead dispatch on each listed value. Output exactly the boxed lambda.', 'mathir':structured['mathir'], 'pantry':structured['pantry'], 'graph_coloring':deliberate['graph_coloring'], }[domain] system=('Solve the executable constraint problem carefully. You may reason briefly, but end with exactly one final answer inside \\boxed{}. '+guidance) return [{'role':'system','content':system},{'role':'user','content':problem}] def countdown_legal_choices(row:dict)->list[str]: """Enumerate syntax-legal expressions without consulting the target or verifier.""" numbers=tuple(str(int(x)) for x in json.loads(str(row['answer']))['numbers']) operators=('+','-','*','/') choices=set() def trees(values,ops): if len(values)==1: return (values[0],) out=[] for split in range(1,len(values)): for left in trees(values[:split],ops[:split-1]): for right in trees(values[split:],ops[split:]): out.append(f'({left} {ops[split-1]} {right})') return tuple(out) for values in set(itertools.permutations(numbers)): for ops in itertools.product(operators,repeat=len(values)-1): choices.update(f'\\boxed{{{expression}}}' for expression in trees(values,ops)) return sorted(choices) def countdown_legal_regex(row:dict)->str: """Compact target-blind regex for every operand permutation and tree shape.""" numbers=tuple(str(int(x)) for x in json.loads(str(row['answer']))['numbers']) operator=r'[+*/-]' def trees(values): if len(values)==1: return (re.escape(values[0]),) out=[] for split in range(1,len(values)): for left in trees(values[:split]): for right in trees(values[split:]): out.append(r'\('+left+' '+operator+' '+right+r'\)') return tuple(out) expressions=set() for values in set(itertools.permutations(numbers)): expressions.update(trees(values)) return r'\\boxed\{(?:'+'|'.join(sorted(expressions))+r')\}' def sampling_params(a,domain:str,row:dict): import vllm guided=None if a.syntax_profile=='countdown_legal_v3' and domain=='countdown': from vllm.sampling_params import GuidedDecodingParams guided=GuidedDecodingParams(regex=countdown_legal_regex(row)) elif a.syntax_profile in ('pantry_legal_v1','domain_legal_v1','domain_legal_v2') and domain=='pantry': from vllm.sampling_params import GuidedDecodingParams spec=json.loads(str(row['answer'])) alternatives=[] for ingredient in spec['ingredients']: ident=str(ingredient['id']) minimum=int(ingredient['min_if_used_g']) available=int(ingredient['available_g']) step=int(ingredient['step_g']) for grams in range(minimum,available+1,step): alternatives.append(f'{ident}={grams}') atom='(?:'+'|'.join(re.escape(x) for x in alternatives)+')' regex=r'\\boxed\{'+atom+'(?:;'+atom+r'){1,3}\}' guided=GuidedDecodingParams(regex=regex) elif a.syntax_profile in ('domain_legal_v1','domain_legal_v2'): from vllm.sampling_params import GuidedDecodingParams boxed={ 'countdown':r'\\boxed\{[0-9 +*/().-]+\}', 'python_factors':r'\\boxed\{lambda n: [A-Za-z0-9 _%<>=!+*/().-]+\}', 'mathir':r'\\boxed\{[A-F](?:;[A-F]){0,3}\}', } optional={ 'countdown':r'(?:\\boxed\{[0-9 +*/().-]+\}|[0-9][0-9 +*/().-]*)', 'python_factors':boxed['python_factors'], 'mathir':r'(?:\\boxed\{[A-F](?:;[A-F]){0,3}\}|[A-F](?:;[A-F]){0,3})', } regex=(boxed if a.syntax_profile=='domain_legal_v1' else optional).get(domain) if regex is not None: guided=GuidedDecodingParams(regex=regex) return vllm.SamplingParams(n=8,temperature=a.temperature,top_p=a.top_p,max_tokens=a.max_tokens,seed=a.seed,guided_decoding=guided) def main(): a=args() if a.output.exists(): raise FileExistsError(f'fresh receipt required: {a.output}') import vllm from datasets import load_from_disk from oat_drgrpo.math_grader import validated_modebench_outcome_key identity=json.loads((a.level2_root/'identity.json').read_text()) if identity.get('decision')!='structurally_admitted_pending_frozen_base_model_viability': raise RuntimeError('Level-2 structural admission is not frozen and passing') if a.domain not in identity['domains']: raise ValueError(a.domain) level1=ROOT/identity['level1_reference'][a.domain]['dev'] rows_by_level={ 'level1':[dict(x) for x in load_from_disk(str(level1))['multi_answer']], 'level2':[dict(x) for x in load_from_disk(str(a.level2_root/a.domain/'dev'))['multi_answer']], } if a.row_limit < 0: raise ValueError('row-limit must be nonnegative') if a.row_limit: rows_by_level={level:rows[:a.row_limit] for level,rows in rows_by_level.items()} llm=vllm.LLM(model=str(a.model.resolve()),dtype=a.dtype,max_model_len=a.max_model_len,gpu_memory_utilization=.82,swap_space=16.0,enable_prefix_caching=True) tokenizer=llm.get_tokenizer() system='Return only the final answer inside \\boxed{}. Do not explain.' results={} for level,rows in rows_by_level.items(): prompts=[tokenizer.apply_chat_template(prompt_messages(a.domain,str(row['problem']),a.prompt_profile),tokenize=False,add_generation_prompt=True) for row in rows] outputs=[] for start in range(0,len(prompts),a.batch_size): batch_rows=rows[start:start+a.batch_size] batch_params=[sampling_params(a,a.domain,row) for row in batch_rows] outputs.extend(llm.generate(prompts[start:start+a.batch_size],batch_params)) if len(outputs)!=len(rows): raise RuntimeError('vLLM output count mismatch') prompt_results=[] for index,(row,out) in enumerate(zip(rows,outputs)): if len(out.outputs)!=8: raise RuntimeError(f'{level}/{index}: expected 8 samples') attempts=[] for sample in out.outputs: text=str(sample.text); key=validated_modebench_outcome_key(text,row['answer']) attempts.append({'text':text,'verified':key is not None,'canonical_key':key,'token_count':len(sample.token_ids)}) prompt_results.append({'row_index':index,'passed':any(x['verified'] for x in attempts),'verified_count':sum(x['verified'] for x in attempts),'attempts':attempts}) success=sum(x['passed'] for x in prompt_results) results[level]={'rows':len(rows),'success_prompts':success,'pass_at_8':success/len(rows),'rows_sha256':sha(rows),'prompt_results':prompt_results} l1=results['level1']['pass_at_8']; l2=results['level2']['pass_at_8'] admitted=.10<=l2<=.90 and l2=.10,'level2_not_too_easy':l2<=.90,'level2_harder_than_level1':l2